Yes absolutely. The natural evolution is making processes smarter. People reconfigured process and managed underlying technology platforms as such but with significant strides in AI and technology capability, changes will be made more and more on the fly by technology. Intelligent automation is taking data analytics, AI, decisioning frameworks, etc mashing it together to affect the process on the fly. In fact intelligent automation is already here.

The evidence supports this - we have hardly scratched the surface with BPM and this should come as no surprise when we see that business strategy methods invented in the late 1950's are just starting to achieve liftoff. e.g. Edith Penrose's Resource Based View.

There have, however, been important exceptions - CPM is an operations-level method and it achieved instant liftoff - it was a finely-tuned machine at the time RBV was introduced. What is remarkable is that CPM is still in use today, pretty much as it was originally designed. I guess the original design was right.

My take is the BPM community needs to move from (BP)M to B(P)M - this would set the stage for blending in AI.

As for RPA, now is the time to get this working for all stakeholders - in our shop we waste countless hours doing copy paste from one window to the next when a simple "watch me while I. . ." could eliminate most of the work.

I would love to see BPM practitioners and clients at B(P)M.

You can read about the benefits of B(P)M over (BP)M. If you don't know what B(P)M is, my blog post is a must read.

Looking at the term "Intelligent Processes" from a BI and even an AI angle, then yes, I do think that those components will play an ever growing role in the BPM landscape.
Feeding data driven events back into processes with either pre-made or ad-hoc scenario handlers, in order to proactively adjust process flows and/or business rules towards accomplishing a dynamic set of business goals, is not only feasible by today's state of BPM technologies but also represents one of the most underutilized capacities of almost any current BPM initiative. The tools for (at least basic) data and process mining are easily available, while the process data, complemented with rich sets of business data, is present too, in most of the cases. So, the reason for not already reaping the fruits of intelligent processes, will likely be related to a still prevalent lack of organizational maturity into that direction and the subsequent willingness to invest in the required data-science which ultimately would enable the path to intelligent "anything", including BPM.

As long as the majority of the organizations has the BPM maturity level of a one-cell organism, venturing into RPA, AI, ML and what more is only a flight forward without securing a sound foundation.First clean up your house, make it strong and then apply domotica (it's an analogy, but you all understand that of course :-) ).

Yes, intelligent automation will for sure have a role in BPM (or (BP)M, B(P)M, I do need to read your blog apparently, @Karl Walter Keirstead# ) but an organization must first ensure it has proper business process governance in place. Here I would like to qoute a movie from this year (John Wick Chapter 2): "Rules, Jonathan, without them we would be living with the animals". Process governance does exactly that, set rules for the organization on how to maintain, optimize and execute processes and then, and only then, look for ways to automate them with RPA, AI, ML and the rest of the alphabet.

4) TECHNOLOGIES OF AUTOMATION -- BPM and RPA are enablers of greater productivity. Everything that a BPM deployment does can be done via pencil and paper.

5) INVESTMENT HURDLE -- Therefore BPM and RPA, like all technologies, are justified on productivity. (One can make an argument that some technologies enable something to be done that was never done before. This is true, but doesn't change the argument.)

6) INVESTMENT CHOICE -- If BPM and RPA enable greater productivity, at a positive NPV, then business executives will invest.

7) COMPETITIVE PRESSURE -- And if business leaders are investing in automation for greater productivity, then the economics and business models for a given sector will change, forcing all market participants to follow suit.

9) MANY UNCERTAINTIES & RISKS IN TECHNOLOGY INVESTMENTS -- There are MANY uncertainties associated with technology investments (let's ignore non-technology uncertainties and risks, such as financial risk, sovereign risk, market risk etc). Technology standards are important because they reduce costs of participation. What standards should I back? What technologies should I choose? There are more technologies and more standards and more proprietary vendors than I have time to fully explore.

10) DECISION COST HIGH -- The cost of researching a given technology decision can be very high. Should I choose a given BPM standard? Is this a proprietary RPA lock-in? What UX framework is implied in these products? Can I find staff to do this work? Are these projects that are so close to our core competency that I should keep them in-house? Or can I outsource some things? Am I a risk-embracing early adopter? Or more conservative in terms of technology adoption?

Decision-making can be assessed in terms of quality of output. Am I making good technology investment decisions? Business executives follow many strategies to help reduce technology decision uncertainty. It's particularly common (and perhaps even helpful) to have a "narrative" roadmap concerning technology directions. Many wealthy organizations will subscribe to analyst services. The phenomenon of "hype" is part of the matrix of decisioning (and not necessarily a bad phenomenon -- think of hype as "community signalling" -- on a good day hype can be a form of risk reduction -- or on a bad day of lemming-like failure).

11) INVESTMENTS IN SMART TECHNOLOGY??? -- Concerning "intelligent", this means AI and ML (and process mining especially), but also decision rules. I need to understand what it is that I am automating. There's a difference between "automating my business" and "automating the production of business process artefacts". A BPM platform is in part a "process artefact manufacturing technology". Can AI help me manufacture more automation artefacts?

So, the question about intelligent automation, BPM and RPA can be understood as a question about technology investments. To be competitive and productive, I need to invest. And to invest wisely, I need to understand technology directions and risks. And my own appetite for risk. The comments above from other BPM.com forum participants are helpful in clarifying these questions. Because it's a really important question! Do I invest in automation or not!!!??

All the above is standard technology investment rubrics, i.e. "Technology Investments 101". But our question concerns BPM and RPA specifically. They are not just any technologies. The question of technology investment is more important where BPM and RPA are concerned than with ("even all"!) other technologies. Let's not miss the absolute uniqueness of BPM and RPA, and especially BPM.

Business process management software technology (“BPM”) is the technology for automating the work of business. By definition, in BPM automation technology, and only in that technology, concepts of work and process are first-class citizens of that technology. So when one is considering technology investment, consider that the stakes are much clearer and much higher when the technology investment under scrutiny is THE technology of automation and productivity.

@Walter -- The typical definition of productivity is "ratio of output value to input costs", e.g. applied to human labour. From an economics perspective, there is no "right way" -- the right way and even "the right thing" evolves over time, under conditions of competition. Insofar as BPM concerns automation and productivity, BPM concerns the organization of work such that productivity improves, i.e. due to better efficiency. As part of a BPM program, an organization may also engage in re-engineering, the better to avoid the anti-pattern of "paving the cow path". In this case, the "right way" evolves.

@John - Thanks. Based on the definition of productivity that you have contributed, we have to say, then, that the formula I found (i.e. "Productivity = Effectiveness + Efficiency") is not right. Not sure I agree with the author's definitions either of effectiveness or efficiency.

@John BPM is the discipline "BPMAT" the support software and yes with right architecture brings automation and productivity. We have found also enables intelligent automation or intelligent processes where decisions can be automated dependant upon past actions. You are of course right "...to invest wisely, I need to understand technology directions and risks." Sadly industry analysts rarely do deep research and certainly not from the real upstart challengers! This forum is now encouraging debate about "how" and as understanding spreads so BPM takes that next step....I live in hope....

RPA is only one aspect of AI with focus on the dynamic presentation of data on a working UI. So yes for RPA but limited. On the other hand BPM is a discipline that covers all aspects of creation and use of information and AI will evolve as opportunities emerge where "machines" can intelligently create data. Understanding the context of both the input and output for AI within the whole business process is important which should trigger the need to articulate that knowledge. I say "should" but the way IT has evolved in the silo dis-functional techie way it is quite likely AI will be just a one off "task" installed without the recognition of those surrounding people tasks where data used and created for the end to end Business Process.

Looking to the future where there is going to be a need for sustainable and transparent assurance where data is created. AI could be the trigger for seeing that bigger picture and thus BPM is a natural discipline covering both creation of AI and the surrounding Business Processes. In addition there is a current move by the accounting profession to refocus what audit and assurance could look like in the future. The Canadian and Scottish professional bodies are currently working together and have just produced a paper "Audit & Assurance in the Future" see link. One area of focus is "Data Capture and Transformation" which brings up Audit Data Analytics (ADAs) which recognises the importance of "determining the integrity of the data obtained. What controls does the company have in place to help enable the auditor to be comfortable with the data? How much work is required over the controls and/or the data to determine its integrity? What procedures are required over the “information produced by the entity”?" Logic suggest a need to focus on back to basics where people and their process including AI create all data and that's where BPM sits. Again understanding AI could trigger this move to be scrutinised by accountants to deliver required assurance?

I do think that those components will play an ever growing role in the BPM landscape. Feeding data driven events back into processes with either pre-made or ad-hoc scenario handlers, in order to proactively adjust process flows and/or business rules towards accomplishing a dynamic set of business goals, is not only feasible by today's state of BPM technologies but also represents one of the most underutilized capacities of almost any current BPM initiative. The tools for (at least basic) data and process mining are easily available, while the process data, complemented with rich sets of business data, is present too, in most of the cases. So, the reason for not already reaping the fruits of intelligent processes, will likely be related to a still prevalent lack of organizational maturity into that direction and the subsequent willingness to invest in the required data-science which ultimately would enable the path to intelligent "anything", including BPM.